One measure of the integrity of a communication system is the amount of noise present within the system. Characterizing the noise of a communication system involves measuring noise power within one or more specified frequency bands, shown for example in the exemplary noise spectrum of FIG. 1. Measuring noise power, in turn, involves measuring or estimating the statistics of the noise, which is inherently random.
A conventional noise figure meter (shown in FIG. 2) provides accurate measurements of noise power within a designated frequency band. In the noise figure meter, noise within the frequency band is down-converted and measured by a noise power detector. Because the noise figure meter includes multiple frequency conversion stages, the noise figure meters are typically expensive to manufacture.
Conventional direct conversion receivers (shown in FIGS. 3A–3B) are also used to measure noise power. A direct conversion receiver is typically less expensive to manufacture than a noise figure meter because the receiver includes only a single frequency conversion stage. The direct conversion receiver converts the noise within a frequency band (for example, frequency band c shown in FIG. 3C) to a baseband noise signal (shown in FIG. 3D) that is measured by a noise power detector (as shown in FIG. 3A) or by a narrow-band analog-to-digital converter (as shown in FIG. 3B). However, these direct conversion receivers are not as accurate as noise figure meters. One measure of error, the variance of the measured noise power, is substantially higher for the direct conversion receiver than for the noise figure meter. For example, the variance of the noise power measured by a typical direct conversion receiver is approximately twice as great as the variance of the noise power measured by a noise figure meter.
An alternative approach to noise power measurement is shown in FIG. 4A. In this approach, a frequency conversion stage causes upper and lower noise sidebands to overlap within a single measurement band B. FIGS. 4B–4D show these overlapping noise sidebands within the single measurement band B as a local oscillator within the frequency conversion stage is stepped in frequency between frequencies f1, f2 and f3. A noise power detector then measures the noise power in the single measurement band B, with the local oscillator at each of the stepped frequencies. While this approach can take advantage of low-cost signal processing to extract the noise power in a designated frequency band (for example, frequency band c) based on the overlapping noise sidebands, measurement accuracy is not as good as that of the conventional noise figure meter. For example, the variance of the noise power measured using this approach is approximately three times as great as the variance that results when noise power is measured using a conventional noise figure meter.
In view of the above, there is a need for an accurate noise measurement system that does not rely on the multiple frequency conversion stages of a noise figure meter.